\section{Quotations}
``predictability is an essential feature of a user interface; without it users
will love the essential feeling of control''
Norman ``how might people inteact with Agents''


\section{Method}
\begin{itemize}
  \item delimit the boundaries: e.g., how far the NL understanding is supposed
  to go? same for the model for bqueries
  
\end{itemize}




\section{Others}
\begin{itemize}
  \item use of a lexicon; lexicon acquisition problem; see ``Acquiring
  Word-Meaning Mappings for Natural Language Interfaces'', 2003, page 10
\end{itemize}






\subsection{Patterns for unstructured data}
Patterns have been extensively used in the \ac{IR} community for extracting
information.  In the context of \ac{QA} systems, similar patterns are used for
answering questions from text corpora.



\subsubsection{Question patterns on the Web; how to make meaningful queries on
the Web?}
Searches over the Web in an enterprise context does not meet the same goals as
that for standard search engines.
The problematic of searching in the enterprise world has been well depicted by
Hawking~\cite{CIE}. 
In our context, Web search is intended to be a complementary source of
information than trusted data warehouses. 
A typical case is that of a data warehouse about KPI\footnote{Key performance
indicator}. 
The analysis of these indicators is crucial to improve performance of the
company. 
In that case, it's also interesting to take into account other information,
like geographic location of retailers, the characteristics of the cities where
they are located, and information about the population, their habits, etc.
Some of these information may be already in the data warehouse, other can be
found on the internet.

\subsubsection{Modifying user's query}
The first step consits in modifying user's query, so that we expand it with
pieces of information that are already available in trusted data warehouses.







Papers of interest:
\begin{itemize}
  \item Personalizing XML Search in PIMENTO~\cite{DBLP:conf/icde/Amer-YahiaFL07}
  \item Personalizing XML Text Search in PIMENT
  \item Personalized Web Search with Location Preferences
  \item Personalizing web search results by reading level
  \item Context-aware search personalization with concept preference
  \item A framework for personalized and collaborative clustering of search
  results
  \item User action interpretation for personalized content optimization in
  recommender systems
  \item Matching task profiles and user needs in personalized web search
  \item Using a graph-based ontological user profile for personalizing search
  \item Gossiping personalized queries
  \item PerK: personalized keyword search in relational databases through
  preferences
  \item 
\end{itemize}



``PIMENTO project which aims at improving the relevance of searching structured
and unstructured content''. 






\section{Introduction}
Personalized systems aim at providing results specific to users.
This means that a query would trigger different result items for different
users. 
Personalized systems belong to configurable systems

Introduce MDX and SQL in the introduction





